1731: Henry Cavendish is born

On 10 October 1731, Henry Cavendish was born in Nice. The shy son of English aristocrats would become one of the most exacting experimental scientists of the Enlightenment and an unlikely forebear of the quantitative spirit that later made artificial intelligence possible.

Cavendish devoted his life to measurement. In a private laboratory he weighed gases with obsessive care, established the composition of water and air, isolated “inflammable air” (hydrogen), and, in 1798, used a torsion balance to determine the density of the Earth. That celebrated Cavendish experiment remains a textbook example of ingenious apparatus and relentless attention to sources of error. He also mapped the behaviour of electricity so thoroughly that he anticipated Ohm’s and Coulomb’s laws, yet he published almost nothing; much of his work lay hidden in notebooks for a century.

Why does an eighteenth-century recluse belong in the deep history of AI? Because modern computing and machine learning rest on the same foundation he helped solidify: the conviction that nature can be captured in precise numbers and that careful, repeatable experiment is the route to reliable knowledge. The engineers who built the first digital machines, the mathematicians who formalised information and statistics, and the researchers who train today’s neural networks all inherited that ethos of quantification and error control.

Cavendish’s hydrogen researches, his gravitational measurements and his electrical investigations fed the scientific culture that eventually supplied both the physical substrate of electronics and the intellectual habits of data-driven inquiry. Without a tradition that prized ever-finer measurement, the digital age would have lacked essential tools and standards.

In contemporary AI laboratories, models are trained on vast curated data sets, parameters are optimised to many decimal places, and success is scored against quantitative benchmarks. The lonely experimenter born on this day nearly three centuries ago would have recognised the obsession with precision, even if the silicon and the algorithms would have left him speechless.